• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.4
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• pp.556-562
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• 2012

Micro electrical discharge machining (${\mu}EDM$) has been used for non-conventional material removal. One drawback of ${\mu}EDM$ is low productivity. In this study, we tried to find the optimal machining conditions to manufacture the micro hole with an optimal machining time without loss of accuracy. Taguchi method was used to figure out the relation between machining parameters and characteristics of the process. It was found that the electrode wear, the entrance and exit clearance gave a significant effect on the diameter of the micro hole when the diameter of the electrode was identical. Grey relational analysis was used to determine the optimal machining condition for minimum machining time without loss of accuracy. The obtained optimal machining condition was the input voltage of 80V, the capacitance of 680pF, the resistance of $500{\Omega}$, the feed rate of $1.5{\mu}m$/s and the spindle speed of 2900rpm. The machining time was reduced to 48% without loss of accuracy under the optimal machining condition.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.4
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• pp.48-53
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• 2009

Inconel 718 alloy, widely used as material of aircraft engine, has a good mechanical property in high temperature, strong anti-oxidation characteristics in oxidated current over $900^{\circ}C$, and also is not easily digested in the air containing sulfur, therefore, its usage as mechanical component is expanding rapidly. Even though Inconel alloy 718 is difficult to machine, it requires highly precise processing/machining to sustain its component quality of high accuracy. In this paper, general turning operation conditions are tested to select the best cutting process condition by measuring surface roughness through implementing experiments with orthogonal array of cutting speed, feeding speed and cutting depth as processing parameters based on the Taguchi method. Optimal turning operation conditions are extracted from the proposed experimental models.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.4726-4731
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• 2011

This paper proposed the algorithm to select optimal grinding condition for plunge grinding in the batch production unit. In order to apply to the proposed algorithm, the state variable for plunge grinding process was defined and the optimal grinding condition for each cycle in batch production was decided by genetic algorithm. Based on the optimized grinding condition in each cycle, the optimal grinding condition for whole batch production was selected by dynamic programming. The proposed algorithm was evaluated by computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1215-1220
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• 2004

Reactive distillation (RD) is a combination process where both separation and reaction are considered simultaneously in a single vessel. This kind of combination to enhance the overall performance is not a new attempt in the chemical engineering areas. The recovery of ammonia in the classic Solvay process for soda ash of the 1860s may be cited as probably the first commercial application of RD. The RD system has been used for a long time as a useful process and recently the importance of the RD is enlarged more and more. In addition to that, the application fields of RD are diversely diverged. To make the most of the characteristic of RD system, we must decide the best operating condition under which the process shows the most effective productivity and should decide the best control algorithm which satisfies an optimal operating condition. Phosgene which is a highly reactive chemical is used for the production of isocyanates and polycarbonates. Because it has high reactivity and toxicity, its utilization is increasingly burdened by growing safety measures to be adopted during its production. Dimethyl Carbonate (DMC) was proposed as a substitute of phosgene because it is non-toxic and environmentally benign chemical. In this study, RD is used for DMC production process and the transesterification is performed inside of column to produce DMC. In transesterification, the methanol and ethylene carbonate (EC) are used as the reactants. This process use homogeneous catalyst and the azeotrope exists between the reactant and product. Owing to azeotrope, we should use two distillation columns. For this DMC production process, we can suggest two configurations. One is EC excess process and the other is methanol excess process. From the comparison of steady state simulation results where the Naphtali-Sandholm algorithm is used, it showed the better performance to use the methanol excess process configuration than EC excess process. Then, the dynamic simulation was performed to be based on the steady state simulation results and the optimal control system was designed. In addition to that, the optimal operating condition was suggested from previous results.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.10
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• pp.31-40
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• 2003

In this paper, optimal cutting condition to minimize the form error in side wall machining with a flat end mill is studied. Cutting forces and tool deflection are calculated considering surface shape generated by the previous cutting such as roughing. Using the form error prediction method from tool deflection, optimal cutting condition considering form accuracy is investigated. Also, the effects of tool teeth number, tool geometry and cutting conditions on form error are analyzed. The characteristics and the difference of generated surface shape in up and down milling are discussed and over-cut free condition in up milling is presented. Form error reduction method through successive up and down milling is also suggested. The effectiveness and usefulness of the presented method are verified from a series of cutting experiments under various cutting conditions. It is confirmed that form error prediction from tool deflection in side wall machining can be used in optimal cutting condition selection and real time surface error simulation for CAD/CAM systems. This study also contributes to cutting process optimization for the improvement of form accuracy especially in precision die and mold manufacturing.

• Journal of Welding and Joining
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• v.24 no.5
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• pp.67-73
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• 2006

Laser welding is suitable for welding to the aluminum alloy sheet. In order to apply the aluminum laser welding to production line, parameters should be optimized. In this study, the optimal welding condition was searched through the genetic algorithm in laser welding of AA5182 sheet with AA5356 filler wire. Second-order polynomial regression model to estimate the tensile strength model was developed using the laser power, welding speed and wire feed rate. Fitness function for showing the performance index was defined using the tensile strength, wire feed rate and welding speed which represent the weldability, product cost and productivity, respectively. The genetic algorithm searched the optimal welding condition that the wire feed rate was 2.7 m/min, the laser power was 4 kW and the welding speed was 7.95 m/min. At this welding condition, fitness function value was 137.1 and the estimated tensile strength was 282.2 $N/mm^2$.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.1038-1043
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• 1997

To adapt the neural network proess for the purpose of determination of optimal utting onditions (optimal cutting speed and feed rate), some selection strategies for the machining factors are necessary, which is considered planning cutting process. In this case, factors that have both nonlinearity and strong relationship must be selected. Although tool grade and chemical properties of workpiece material have strong effect to cutting speed, it's not easy to find a analytic relation between them. In this paper, a mathematical method for determining the optimal amount of cutting (depth of cut, feed rate) is presented by tool goemetry and heat generation during cutting process. And various tool grade and workpiece material groups ase classified based on its chemical properties. Thier chemical composition and hardness are used as input pattern for neural network learnig. The result of learning shows the relationship between tool grade and workpiece material and it is proved that it can be used as a sub-system for automatic process planning system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.129-139
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• 2019

In order for a gun-launched guided projectile to glide to the maximum range, when to deploy the fin and start flight with guidance and control should be considered in range optimization process. This study suggests a solution to the optimal guidance problem for flight range maximization of the flight model of a guided projectile in vertical plane considering the aerodynamic properties. After converting the nonlinear Multi-Phase Optimal Control Problem to Two-Point Boundary Value Problem, the optimized guidance command and the best fin deployment timing are calculated by the proposed numerical method. The optimization results of the multiple flight rounds with various initial velocity and launch angle indicate that determining specific launch condition incorporated with the guidance scheme is of importance in terms of mechanical energy consumption.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2002.02a
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• pp.61-67
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• 2002

The present work is investigated optimal design for the injection molding process of a hand brake cover. The viscoelastic flow through a hand brake cover shape in the mold were calculated and compared with the experimental data. Numerical analysis reasonably predicted the general performance i.e hold pressure, cooling time and hold pressure time. In order to determine optimal process parameters, Numerical analysis and experiments have been performed for various process conditions. In this study, we obtained to increase in the productivity by $160\%$ by optimal process conditions.

• Journal of Welding and Joining
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• v.18 no.5
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• pp.63-69
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• 2000

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables was wire feed rate, welding voltage, and welding speed and the output variables were bead height, bead width, and penetration. The number of level for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 40 experiments.